Routing scorecard

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description fully discloses behavior: it reads board data, computes metrics, and provides advice only. It matches the readOnlyHint annotation and adds details about data sources, metrics, and the 'no verdict' policy. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the primary verb and resource. It uses a logical structure: purpose, metrics, caveats, and sibling references. Slightly verbose but each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description extensively covers what the tool returns: metrics per tier cross-cut by effort, and the 'insufficient data' case. It also explains data sources, the advisory nature, and pairing suggestions. Comprehensive for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Description adds value for minSamples (default 3, minimum 1) and windowDays (why to limit recency). But project parameter lacks description in both schema and description. Schema coverage is 67%, so description partially compensates but not fully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to score tickets and report which model tier should run them. It uses specific verbs like 'score' and 'report', and distinguishes from siblings (plan_budget, daily_plan) by naming them and contrasting. The first sentence captures the core action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool: to determine the best tier for ticket sizes. It gives context about insufficient data for low-sample tiers and explicitly states it does not write labels. However, it does not provide explicit exclusions or alternatives beyond mentioning sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.